TY - JOUR
T1 - Confidence limits on one-stage model parameters in benchmark risk assessment
AU - Buckley, Brooke E.
AU - Piegorsch, Walter W.
AU - West, R. Webster
N1 - Funding Information:
Acknowledgements This research was initiated while all the authors were with the University of South Carolina. Thanks are due Drs. Obaid M. Al-Saidy, Ralph L. Kodell, and Daniela K. Nitcheva for their invaluable support to the project, and two external reviewers for their helpful comments. This work was funded under grant #R01-CA76031 from the U.S. National Cancer Institute, grant #RD-83241901 from the U.S. Environmental Protection Agency, and as part of the research arm of the U.S. Department of Homeland Security’s Center of Excellence for the Study of Terrorism and Responses to Terrorism (START). Its contents are solely the responsibility of the authors and do not necessarily reflect the official views of these various agencies.
PY - 2009
Y1 - 2009
N2 - In modern environmental risk analysis, inferences are often desired on those low dose levels at which a fixed benchmark risk is achieved. In this paper, we study the use of confidence limits on parameters from a simple one-stage model of risk historically popular in benchmark analysis with quantal data. Based on these confidence bounds, we present methods for deriving upper confidence limits on extra risk and lower bounds on the benchmark dose. The methods are seen to extend automatically to the case where simultaneous inferences are desired at multiple doses. Monte Carlo evaluations explore characteristics of the parameter estimates and the confidence limits under this setting.
AB - In modern environmental risk analysis, inferences are often desired on those low dose levels at which a fixed benchmark risk is achieved. In this paper, we study the use of confidence limits on parameters from a simple one-stage model of risk historically popular in benchmark analysis with quantal data. Based on these confidence bounds, we present methods for deriving upper confidence limits on extra risk and lower bounds on the benchmark dose. The methods are seen to extend automatically to the case where simultaneous inferences are desired at multiple doses. Monte Carlo evaluations explore characteristics of the parameter estimates and the confidence limits under this setting.
KW - Benchmark dose
KW - Bootstrap
KW - Dose - response model
KW - Environmental risk analysis
KW - Quantal dose response
KW - Quantitative risk assessment
KW - Resampling
KW - Simultaneous inferences
KW - Weibull
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U2 - 10.1007/s10651-007-0076-2
DO - 10.1007/s10651-007-0076-2
M3 - Article
AN - SCOPUS:59649107463
SN - 1352-8505
VL - 16
SP - 53
EP - 62
JO - Environmental and Ecological Statistics
JF - Environmental and Ecological Statistics
IS - 1
ER -